
# Importing necessary libraries

import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import plotly.express as px
import plotly.graph_objects as go

pd.set_option('display.max_columns', None)


# Loading data

df = pd.read_csv("D:/Softwares/DS/Project/FootballData/PL 2019-2020/Premier_league_19_20.csv")


# Viewing top 5 records

df.head()


# Getting columns names 

df.columns

Index(['date', 'home_team', 'away_team', 'home_score', 'away_score',
       'home_possession_%', 'away_possession_%', 'home_shots_on_target',
       'away_shots_on_target', 'home_shots', 'away_shots', 'home_touches',
       'away_touches', 'home_passes', 'away_passes', 'home_tackles',
       'away_tackles', 'home_clearances', 'away_clearances', 'home_corners',
       'away_corners', 'home_offsides', 'away_offsides', 'home_yellow_cards',
       'away_yellow_cards', 'home_red_cards', 'away_red_cards',
       'home_fouls_conceded', 'away_fouls_conceded'],
      dtype='object')


# Basic info of data

df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 380 entries, 0 to 379
Data columns (total 29 columns):
 #   Column                Non-Null Count  Dtype  
---  ------                --------------  -----  
 0   date                  380 non-null    object 
 1   home_team             380 non-null    object 
 2   away_team             380 non-null    object 
 3   home_score            380 non-null    int64  
 4   away_score            380 non-null    int64  
 5   home_possession_%     380 non-null    float64
 6   away_possession_%     380 non-null    float64
 7   home_shots_on_target  380 non-null    float64
 8   away_shots_on_target  380 non-null    float64
 9   home_shots            380 non-null    float64
 10  away_shots            380 non-null    float64
 11  home_touches          380 non-null    float64
 12  away_touches          380 non-null    float64
 13  home_passes           380 non-null    float64
 14  away_passes           380 non-null    float64
 15  home_tackles          380 non-null    float64
 16  away_tackles          380 non-null    float64
 17  home_clearances       380 non-null    float64
 18  away_clearances       380 non-null    float64
 19  home_corners          380 non-null    float64
 20  away_corners          380 non-null    float64
 21  home_offsides         380 non-null    float64
 22  away_offsides         380 non-null    float64
 23  home_yellow_cards     380 non-null    float64
 24  away_yellow_cards     380 non-null    float64
 25  home_red_cards        380 non-null    float64
 26  away_red_cards        380 non-null    float64
 27  home_fouls_conceded   380 non-null    float64
 28  away_fouls_conceded   380 non-null    float64
dtypes: float64(24), int64(2), object(3)
memory usage: 86.2+ KB


# Statistical summary

df.describe()

# (Here it can be seen that min value for each row is 0 which can't be true, might be few missing value in the data or any 
#  other issue)


# Checking for missing value

df.isnull().sum()

# No missing value in the data
# (Will have to look other way round to check why min value for each col is 0 in statistical summary)

date                    0
home_team               0
away_team               0
home_score              0
away_score              0
home_possession_%       0
away_possession_%       0
home_shots_on_target    0
away_shots_on_target    0
home_shots              0
away_shots              0
home_touches            0
away_touches            0
home_passes             0
away_passes             0
home_tackles            0
away_tackles            0
home_clearances         0
away_clearances         0
home_corners            0
away_corners            0
home_offsides           0
away_offsides           0
home_yellow_cards       0
away_yellow_cards       0
home_red_cards          0
away_red_cards          0
home_fouls_conceded     0
away_fouls_conceded     0
dtype: int64


# Checking for 'home_possession_%' column because almost other stats like home_score, away_score, home_shots_on_target etc 
# can be 0 but stats like away_possession_%, home_possession_%, home_passes can't be 0

df[df['home_possession_%'] == 0]

# (Baaamm!! So here is the issue in the data. Stats of few matches are missing so they are recorded as 0 and hence min value
#  for each column in statistical summary is 0)


# Removing all the above records which were recorded as 0 

df1 = df[~(df['home_possession_%'] == 0)]


df1[df1['home_possession_%'] == 0]

# Successfully removed


df1.describe()

# Got rid of all the 0's of minimum count for each columns


# Getting only home and away matches played by Liverpool

Liverpool_19_20_matches = df1[(df1['home_team'] == 'Liverpool') | (df1['away_team'] == 'Liverpool')]
Liverpool_19_20_matches.head(3)

# (Here it can be seen that the data has no record of which team won or lost)


# Creating conditions to apply on Liverpool_19_20_matches to get new column informing Won, Lost or Draw

conditions = [
                (Liverpool_19_20_matches['home_score'] > Liverpool_19_20_matches['away_score']) & (Liverpool_19_20_matches['home_team'] == 'Liverpool'),
                (Liverpool_19_20_matches['away_score'] > Liverpool_19_20_matches['home_score']) & (Liverpool_19_20_matches['away_team'] == 'Liverpool'),
                (Liverpool_19_20_matches['home_score'] == Liverpool_19_20_matches['away_score']),
                (Liverpool_19_20_matches['home_score'] < Liverpool_19_20_matches['away_score']) & (Liverpool_19_20_matches['home_team'] == 'Liverpool'),
                (Liverpool_19_20_matches['away_score'] < Liverpool_19_20_matches['home_score']) & (Liverpool_19_20_matches['away_team'] == 'Liverpool')
             ]


# Create a list of the values we want to assign for each condition

values = ['Liverpool Won', 'Liverpool Won', 'Draw', 'Liverpool Lost', 'Liverpool Lost']


# Create a new column and use np.select to assign values to it using our lists as arguments

Liverpool_19_20_matches['match_result'] = np.select(conditions, values)

C:\ProgramData\Anaconda3\lib\site-packages\ipykernel_launcher.py:3: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  This is separate from the ipykernel package so we can avoid doing imports until


# Viewing top 2 records to check if the new column got added to the dataframe or not

Liverpool_19_20_matches.head(2)


# Grouping few columns to check whether or not the logic applied using np.select holds true for the matches 

Liverpool_19_20_matches.groupby(['home_team', 'home_score', 'away_team', 'away_score', 'match_result']).size().reset_index()


Liverpool_home = Liverpool_19_20_matches[(Liverpool_19_20_matches['home_team'] == 'Liverpool')]
Liverpool_home


Liverpool_home['home_score'].sum()

# Liverpool scored 52 goals at their home,  against all the teams.

52


Liverpool_home['away_score'].sum()

# Liverpool only conceded 16 goals at their home

16


Liverpool_home['home_possession_%'].mean()

# Liverpool had the possession of 63% at Home in the overall 2019-2020 season.

62.18947368421052


Liverpool_home['away_possession_%'].mean()

# Liverpool's apponent managed to keep only 38% possession at Liverpool's Home.

37.81052631578948


Liverpool_home['home_shots'].sum()

# Liverpool had 314 shots while playing at Home

314.0


Liverpool_home['home_shots_on_target'].sum()

# Out of 314 total shots, Liverpool shooted 129 shots on target.

129.0


Liverpool_home['away_shots'].sum()

# Liverpools opponent were allowed 172 shots at Anfield.

172.0


Liverpool_home['away_shots_on_target'].sum()

# Out of 172 total shots, opponent managed only to shoot 58 shots on target.

58.0


Liverpool_home['home_passes'].sum()

# Liverpool passed 11821 no. of passes throughout 19-20 season.

11821.0


Liverpool_home['away_passes'].sum()

# Liverpool's opponent managed 7087 no. of passes when playing against Liverpool at Anfiled.

7087.0


Liverpool_home['home_tackles'].sum()

# Liverpool tackled 295 times at home.

295.0


Liverpool_home['away_tackles'].sum()

# Opponent teams tackled 293 times on Liverpool players.

293.0


Liverpool_home['home_clearances'].sum()

# No. of clearances made by Liverpool are 288

288.0


Liverpool_home['away_clearances'].sum()

# No. of clearances made by opponent teams are 560. These are high because of the no. of shots

560.0


Liverpool_home['home_corners'].sum()

# Liverpool got 143 corners

143.0


Liverpool_home['away_corners'].sum()

# Whereas oppponent teams got 92 corners

92.0


Liverpool_home['home_offsides'].sum()

# Liverpool were 31 times offside at home.

31.0


Liverpool_home['away_offsides'].sum()

# Opponent team were 76 times offside.

76.0


Liverpool_home['home_yellow_cards'].sum()

# 13 yellow cards were given to Liverpool players for making foul.

13.0


Liverpool_home['away_yellow_cards'].sum()

# 27 yellow cards were given to opponent teams for making foul.

27.0


Liverpool_home['home_red_cards'].sum()

# Liverpool player got 1 red card for causing a severe foul.

1.0


Liverpool_home['away_red_cards'].sum()

# Opponent teams player didn't recieve a single red card while playing against Liverpool at Anfield.

0.0


Liverpool_home['home_fouls_conceded'].sum()

# Total no. of fouls conceded by Livepool are 156 out of which 13 Yellow cards and 1 Red card was given.

156.0


Liverpool_home['away_fouls_conceded'].sum()

# Total no. of fouls conceded by opponent teams are 170 out of which 27 were given as Yellow cards.

170.0


Liverpool_away = Liverpool_19_20_matches[(Liverpool_19_20_matches['away_team'] == 'Liverpool')]
Liverpool_away


Liverpool_away['away_score'].sum()

# Liverpool scored 33 goals while playing away (NOT at their home)

33


Liverpool_away['home_score'].sum()

# Liverpool conceded 17 goals while playing away

17


Liverpool_away['away_possession_%'].mean()

# Liverpool hold the ball 65% while playing away.

64.4578947368421


Liverpool_away['home_possession_%'].mean()

# Opponent teams had the possession of 36%.

35.542105263157886


Liverpool_away['away_shots'].sum()

# Liverpool's total no. of shots at away stadiums are 277.

277.0


Liverpool_away['away_shots_on_target'].sum()

# Liverpool's total no. of shots on target at away are 102.

102.0


Liverpool_away['home_shots'].sum()

# Opponent teams managed to shoot total of 169 shots.

169.0


Liverpool_away['home_shots_on_target'].sum()

# Opponent teams total no. of shots on target are 51

51.0


Liverpool_away['away_passes'].sum()

# Total no. of ball passed by Liverpool team are 12051.

12051.0


Liverpool_away['home_passes'].sum()

# Total no. of ball passed by opponent team are 6547

6547.0


Liverpool_away['away_tackles'].sum()

# Liverpool tackled 255 times at away

255.0


Liverpool_away['home_tackles'].sum()

# Opponent team tackled 284 times to Liverpool players.

284.0


Liverpool_away['away_clearances'].sum()

# 299 times Liverpool cleared the ball and prevented the opponent team to not score the goal. (prevented to not take the shot)

299.0


Liverpool_away['home_clearances'].sum()

# Opponent teams cleared the ball 534 times and prevented Liverpool to not the score the goal

534.0


Liverpool_away['away_corners'].sum()

# 114 corners were given to Liverpool while playing away.

114.0


Liverpool_away['home_corners'].sum()

# Opponent teams got 68 corners while playing against Liverpool.

68.0


Liverpool_away['away_offsides'].sum()

# Total no. of offsides that were done by Liverpool are 22.

22.0


Liverpool_away['home_offsides'].sum()

# Opponent teams were 66 times offside while playing against Liverpool.

66.0


Liverpool_away['away_yellow_cards'].sum()

# Total no. of yellow cards that were shown to Liverpool in the season 19-20 are 25.

25.0


Liverpool_away['home_yellow_cards'].sum()

# Opponent team were given 20 yellow cards.

20.0


Liverpool_away['away_red_cards'].sum()

# Liverpool got no red card while playing away.

0.0


Liverpool_away['home_red_cards'].sum()

# Even opponent got no red card.

0.0


Liverpool_away['away_fouls_conceded'].sum()

# Total no. of fouls done by Liverpool are 175 out of which 25 are yellow cards and 0 red card.

175.0


Liverpool_away['home_fouls_conceded'].sum()

# Total no. of fouls committed by opponent's are 152 out of which 20 were given as Yellow card while no red card was given.

152.0


Liverpool_home.head(3)


# Bar plot to see the no. of goals Liverpool scored against each team while playing at Home in 19-20 season.

sns.set(rc = {'figure.figsize':(10,5)})
sns.set(style="darkgrid", color_codes=True)

sns.barplot(x='home_score', y='away_team', data=Liverpool_home, palette="ch:s=.25", edgecolor='pink')

plt.title('Goals Scored By Liverpool when playing at Anfield - ')
plt.show()


# ------------------------------------Observation based on the graph---------------------------------------------

# Most no. of goals scored by Liverpool is 5, against two teams : Everton and Chelsea
# Followed by 4 goals against three teams : Norwich City, Southampton and Crystal Palace
# Followed by 3 goals against four teams : Arsenal, Newcastle United, Manchester City and West Ham United
# Least no. of goals scored by Liverpool is 1, against two teams : Wolves and Burnley
# Majority of times Liverpool scored 2 goals against the opponent team

# Key-Point : Their is not a single team against which Liverpool has scored 0 goal while playing at Home.


# Plotting bar plot to see the no. of goals Opponent team scored against Liverpool while playing at Home in 19-20 season.

sns.set(rc = {'figure.figsize':(10,5)})
sns.set(style="darkgrid", color_codes=True)

sns.barplot(x='away_score', y='away_team', data=Liverpool_home, palette="crest", edgecolor='skyblue')

plt.title('Goals Scored By Opponent Team when playing at Anfield- ')
plt.show()


# ------------------------------------Observation based on the graph---------------------------------------------

# Chelsea scored most no. of goals against Liverpool : 3 goals
# Followed by 2 goals against Liverpool : Everton and West Ham United
# Majority of teams managed to score only 1 goal against Liverpool at Home.

# Key-Point : Most of the teams could not score even single goal against Liverpool.


# Scatter plot to see the ball possession by Liverpool against each team while playing at Home in 19-20 season.

fig = px.scatter(Liverpool_home, x="home_possession_%", y="away_team", color='away_team', size='home_possession_%',
                 title = "Liverpool's Possession against each team -")
fig.show()


# ------------------------------------Observation based on the graph---------------------------------------------

# Most possession(70-75%) Liverpool has against teams : Newcastle United, Sheffield United, AFC Bournemouth, Crystal Palace, Aston Villa, Burnely
# Least Possession(44-50%) Liverpool has against teams : Man City, Brighton and Chelsea

# Key Point : Man City, Brighton and Chelsea has more possession when playing against Liverpool at Home in 19-20 season.
            # Even after having more possession than Liverpool above all 3 teams lost the match at Liverpool's Home.


# Bar plot to see the Home Shots and Home Shots On Target by Liverpool against each team while playing at Home in 19-20 season.

fig = px.bar(Liverpool_home, y="away_team", x=["home_shots", "home_shots_on_target"], barmode='group',
             title='Total Home Shots and Shots On Target by Liverpool against each team -')
fig.show()


# ------------------------------------Observation based on the graph---------------------------------------------

# Most no. of Shots(25) Liverpool has are against West Ham United and Arsenal followed by Burnley(23), Crystal Palace(21), Tottenham(21) and Newscastle United(21)
# Most no. of Shots On Target are against Tottenham(13), Burnley(9), Southampton(9) and Newscastle United(9)
# Least no. of Shots are against Aston Villa(6) followed by Chelsea(10) and Wolves(10) 
# Least no. of Shots On Target are against Wolves(3), Aston Villa(4), Manchester United(5) and Arsenal(5)

# Key-Point : Despite having least no. of shots(10) and least no. of shots on target(7) against Chelsea, Liverpool scored 5 goals against them.


# Bar plot to see the Away Shots and Away shots on target by Opponent team on Liverpool while playing at Home in 19-20 season.

fig = px.bar(Liverpool_home, y="away_team", x=["away_shots", "away_shots_on_target"], barmode='group',
             title='Total Away Shots and Shots On Target by all teams against Liverpool -',
             color_discrete_sequence=px.colors.qualitative.T10_r)
fig.show()


# ------------------------------------Observation based on the graph---------------------------------------------

# Most no. of Shots against Liverpool are by Man City(18) followed by Southampton(17), Everton(12), Brighton(12) and Norwich City(12) 
# Most no. of Shots On Target against Liverpool are by Chelsea(5), Brighton(5) and Norwich City(5)
# Least no. of Shots against Liverpool are by Leicester City(2) followed by Crystal Palace(3) and Sheffield United(3)
# Least no. of Shots On Target against Liverpool are by Crystal Palace(0) followed by Leicester City(1) and Newcastle United(1)

# Key-Point : Despite having only 1 Shot On Target, both Leicester City and Newcastle United managed to score 1 goal against Liverpool but could not win or drew the match.


# Bar plot to see the Home Passes(made by Liverpool team) and Away Passes(made by opponent team) while playing at Liverpool's Home in 19-20 season.

fig = px.bar(Liverpool_home, y="away_team", x=["home_passes", "away_passes"], barmode='group',
             title="Home Passes and Away Passes at Liverpool's Home -",
             color_discrete_sequence=px.colors.qualitative.Dark24_r)
fig.show()

# ------------------------------------Observation based on the graph---------------------------------------------

# Most passes Liverpool made were against Sheffield United(969) followed by Crystal Palace(886) and Newcastle United(847)
# Least passes Liverpool made were against Man City(416), Brighton(482) then Everton(501) and Manchester United(509)
# Most passes made by opponent team against Liverpool are 592 made by Brighton followed by Chelsea(575)
# Least passes made by opponent team against Liverpool are 246 made by AFC Bournemouth followed by Aston Villa(263) and Burnley(265)


# Dumbble Chart to compare Home Tackles vs Away Tackles

Liverpool_home.reset_index(drop=True, inplace=True)

fig = go.Figure()
fig.add_trace(go.Scatter(x = Liverpool_home["home_tackles"], 
                          y = Liverpool_home["away_team"],
                          mode = 'markers',
                          marker_color = 'red',
                          marker_size = 12,
                          name = 'Home Tackles'))
fig.add_trace(go.Scatter(x = Liverpool_home["away_tackles"], 
                          y = Liverpool_home["away_team"],
                          mode = 'markers',
                          marker_color = 'grey', 
                          marker_size = 10,
                          name = 'Away Tackles'))
for i in range(0, len(Liverpool_home)):
               fig.add_shape(type='line',
                              x0 = Liverpool_home["home_tackles"][i],
                              y0 = i,
                              x1 = Liverpool_home["away_tackles"][i],
                              y1 = i,
                              line=dict(color='brown', width = 2))
fig.update_layout(title_text =
                    "Home Tackles vs Away Tackles -"
                    )
#fig.update_xaxes(range=[300, 1200])
fig.show()

# ------------------------------------Observation based on the graph---------------------------------------------

# Most Home Tackles(made by Liverpool) were against Arsenal(25) followed by West Ham United(23) then Manchester United(22)
# Least Home Tackles(made by Liverpool) were against Sheffield United(6) followed by Aston Villa and AFC Bournemouth (7)
# Most Away Tackles(made by Opponent) were by teams Wolves(23) followed by Watford(21) then Crystal Palace and Newcastle United (20)
# Least Away Tackles(made by Opponent) were by teams Aston Villa(8) followed by AFC Bournemouth(9) and Chelsea(9)

# Key-Point : Brighton and Liverpool made same number of tackles.


# Dumbble Chart to compare Home Clearances vs Away Clearances

fig = go.Figure()
fig.add_trace(go.Scatter(x = Liverpool_home["home_clearances"], 
                          y = Liverpool_home["away_team"],
                          mode = 'markers',
                          marker_color = 'red',
                          marker_size = 12,
                          name = 'Home Clearances'))
fig.add_trace(go.Scatter(x = Liverpool_home["away_clearances"], 
                          y = Liverpool_home["away_team"],
                          mode = 'markers',
                          marker_color = 'orange', 
                          marker_size = 10,
                          name = 'Away Clearances'))
for i in range(0, len(Liverpool_home)):
               fig.add_shape(type='line',
                              x0 = Liverpool_home["home_clearances"][i],
                              y0 = i,
                              x1 = Liverpool_home["away_clearances"][i],
                              y1 = i,
                              line=dict(color='skyblue', width = 2))
fig.update_layout(title_text =
                    "Home Clearances vs Away Clearances -"
                    )
fig.show()

# ------------------------------------Observation based on the graph---------------------------------------------

# Most Home Clearances(made by Liverpool) were against Manchester City(27) followed by Leicester City(25) and Everton(25)
# Least Home Clearances(made by Liverpool) were against Crystal Palace(1) followed by Norwich City(5) then Tottenham Hotspur(8) and Newcastle United(8)
# Most Away Clearances(made by Opponent) were by teams AFC Bournemouth(43) and West Ham United(43) followed by Crystal Palace(37) and Burnley(36)
# Least Away Clearances(made by Opponent) were by teams Chelsea(15) and Everton(15) followed by Brighton(20) and Wolves(20)

# Key-Point : Manchester City was the most threatening team in attack whereas Crystal Palace was least threatening while playing at Liverpool's home.
            # AFC Bournemouth and West Ham United were good in defence as they cleared the most no. chances to score whereas Chelsea and Everton were average in thier defence.


# Dumbble Chart to compare Home Corners vs Away Corners

fig = go.Figure()
fig.add_trace(go.Scatter(x = Liverpool_home["home_corners"], 
                          y = Liverpool_home["away_team"],
                          mode = 'markers',
                          marker_color = 'red',
                          marker_size = 12,
                          name = 'Home Corners'))
fig.add_trace(go.Scatter(x = Liverpool_home["away_corners"], 
                          y = Liverpool_home["away_team"],
                          mode = 'markers',
                          marker_color = 'black', 
                          marker_size = 10,
                          name = 'Away Corners'))
for i in range(0, len(Liverpool_home)):
               fig.add_shape(type='line',
                              x0 = Liverpool_home["home_corners"][i],
                              y0 = i,
                              x1 = Liverpool_home["away_corners"][i],
                              y1 = i,
                              line=dict(color='grey', width = 2))
fig.update_layout(title_text =
                    "Home Corners vs Away Corners -"
                    )
#fig.update_xaxes(range=[300, 1200])
fig.show()

# ------------------------------------Observation based on the graph---------------------------------------------

# Most Home Corners(made by Liverpool) were against West Ham United(16) followed by Burnley(11), Manchester United(11) and Norwich City(11)
# Least Home Corners(made by Liverpool) were against Brighton(4), Manchester City(4) and Leicester City(4) followed by Wolves(5) and Everton(5)
# Most Away Corners(made by Opponent) were by teams Manchester City(13) followed by Sounthampton(11)
# Least Away Corners(made by Opponent) were by teams Chelsea(0) and Crystal Palace(0) followed by Newcastle United(1) and Norwich City(2)


# Bar Plot to see the Home Fouls Conceded(including Yellow and Red Card) and Away Fouls Conceded(including Yellow and Red Card)

fig = px.bar(Liverpool_home, y="away_team", x=["home_fouls_conceded", "home_red_cards", "home_yellow_cards",
                                              "away_fouls_conceded", "away_red_cards", "away_yellow_cards"], 
             barmode='stack',
             title="Home Fouls Conceded vs Away Fouls Conceded (including Yellow and Red card) at Liverpool's Home -",
             color_discrete_sequence=px.colors.qualitative.G10_r)
fig.show()

# ------------------------------------Observation based on the graph---------------------------------------------

# Most Home Foul are conceded against Aston Villa(18) followed by Everton(13)
# Least Home Foul are conceded against Brighton(3) followed by West Ham United(4)
# Most Yellow Card Liverpool players got were against Tottenham(3) followed by Watford(2)
# Liverpool player got 0 Yellow Card against Crystal Palace, AFC Bournemouth, West Ham United, Southampton, Sheffield United, Brighton, Manhester City, Newcastle United and Norwich City
# Liverpool player got 1 Red Card against Brighton

# Most Away Fouls(Opponent team) were done by Everton(17) and Leicester City(17) followed by Southampton(15)
# Least Away Fouls(Opponent team) were done by Wolves(3) followed by Burnley(4) amd Newcastle United(4)
# Away Team which conceded Most Yellow Card are Leicester City(4) followed by West Ham United(3),Manchester United(3) and Tottenham(3)
# Least Yellow Card(0) conceded by Away Teams are Chelsea, Crystal Palace, Sheffield United, Wolves, Brighton and Newcastle United
# Away team got no red card(0) while playing against Liverpool at Liverpool's Home.

# Key-Points : Following are the matches with NO Yellow Card and Red Card - 
             # LFC vs Crystal Palace , LFC vs Sheffield United , LFC vs Newcastle United


# Pie plot to see the match result when Liverpool played at Home

print('List of Teams Liverpool won against -\n\n', Liverpool_home.groupby(['away_team','match_result']).size().reset_index().rename(columns={0:'Count'}))
print('-'*70)
print('\nNo. of matches Liverpool Won/Lost or Drawn -\n', Liverpool_home['match_result'].value_counts())
print('-'*70)

fig = px.pie(Liverpool_home, names='match_result' ,
             color='match_result' ,
             color_discrete_map={'Liverpool Won':'lightgreen',
                                 'Draw':'orange',
                                 'Liverpool Lost':'lightcyan'} ,
             title='Match Result when Liverpool played at Home -')
fig.update_layout(
                    autosize=False,
                    width=550,
                    height=400
                )
fig.show()

# ------------------------------------Observation based on the graph---------------------------------------------

# Out of total 19 matches played at Liverpool's Home, Liverpool won 94.7% of matches i.e, 18 matches.
# Liverpool drew only 1 match out of all 19 ,against Burnley.

# Key-Point : Liverpool has not lost a single match when played at Anfield in 2019-2020 season.

List of Teams Liverpool won against -

                    away_team   match_result  Count
0            AFC Bournemouth  Liverpool Won      1
1                    Arsenal  Liverpool Won      1
2                Aston Villa  Liverpool Won      1
3   Brighton and Hove Albion  Liverpool Won      1
4                    Burnley           Draw      1
5                    Chelsea  Liverpool Won      1
6             Crystal Palace  Liverpool Won      1
7                    Everton  Liverpool Won      1
8             Leicester City  Liverpool Won      1
9            Manchester City  Liverpool Won      1
10         Manchester United  Liverpool Won      1
11          Newcastle United  Liverpool Won      1
12              Norwich City  Liverpool Won      1
13          Sheffield United  Liverpool Won      1
14               Southampton  Liverpool Won      1
15         Tottenham Hotspur  Liverpool Won      1
16                   Watford  Liverpool Won      1
17           West Ham United  Liverpool Won      1
18   Wolverhampton Wanderers  Liverpool Won      1
----------------------------------------------------------------------

No. of matches Liverpool Won/Lost or Drawn -
 Liverpool Won    18
Draw              1
Name: match_result, dtype: int64
----------------------------------------------------------------------


Liverpool_away.head(3)


# Bar plot to see the no. of goals Liverpool scored against each team while playing Away in 19-20 season.

sns.set(rc = {'figure.figsize':(10,5)})
sns.set(style="darkgrid", color_codes=True)

sns.barplot(x='away_score', y='home_team', data=Liverpool_away, palette="rocket", edgecolor='red')

plt.title('Goals Scored By Liverpool(Away) - ')
plt.show()


# ------------------------------------Observation based on the graph---------------------------------------------

# Most no. of goals by Liverpool is 4 which was scored against Leicester City.
# Followed by 3 goals against four teams : Burnley, AFC Bournemouth, Brighton and Newcastle United.
# Majority of the times Liverpool scored 2 goals against the opponent team.

# Key-Point : Liverpool scored 0 goal against Watford, Everton and Manchester City while playing at their respective home.


# Bar plot to see the no. of goals Opponent team scored against Liverpool while playing Away in 19-20 season.

sns.set(rc = {'figure.figsize':(10,5)})
sns.set(style="darkgrid", color_codes=True)

sns.barplot(x='home_score', y='home_team', data=Liverpool_away, palette="mako", edgecolor='blue')

plt.title('Goals Scored By Opponent while playing at their respective Home - ')
plt.show()


# ------------------------------------Observation based on the graph---------------------------------------------

# Manchester City scored most no. of goals against Liverpool : 4 goals , followed by Watford : 3 goals
# Majority of teams managed to score  1 goal against Liverpool at their respective Home.

# Key-Point : Most of the teams could not score even single goal against Liverpool.


# Scatter plot to see the ball possession by Liverpool against each team while playing at Home in 19-20 season.

fig = px.scatter(Liverpool_away, x="away_possession_%", y="home_team", color='home_team', size='away_possession_%',
                 title = "Liverpool's Possession against each team when playing Away -")
fig.show()


# ------------------------------------Observation based on the graph---------------------------------------------

# Most possession(70-75%) Liverpool has against teams : Newcastle United, Sheffield United, AFC Bournemouth, West Ham United, Aston Villa, Watford and Everton
# Least Possession(44-50%) Liverpool has against teams : Chelsea

# Key Point : Chelsea, Man City and Wolves has more possession when playing against Liverpool at thier respective Home in 19-20 season.


# Bar plot to see the Away Shots and Away Shots On Target by Liverpool against each team while playing Away in 19-20 season.

fig = px.bar(Liverpool_away, y="home_team", x=["away_shots", "away_shots_on_target"], barmode='group',
             title='Total Home Shots and Shots On Target against each team by Liverpool(Away) -',
             color_discrete_sequence=px.colors.qualitative.Bold_r)
fig.show()


# ------------------------------------Observation based on the graph---------------------------------------------

# Most no. of Shots(25) Liverpool has are against Aston Villa(25) followed by Arsenal(24) then AFC Bournemouth(21) and further Brighton(20)
# Most no. of Shots On Target are against AFC Bournemouth(9) followed by Arsenal(8) and Brighton(8) then Tottenham(7) at their respective Home
# Least no. of Shots are against Chelsea(6) followed by Watford(7), Everton(10) and Manchester City(11)
# Least no. of Shots On Target are against Watford(1) followed by Chelsea(3), Everton(3) and Manchester City(3)

# Key-Point : Out of all the games where Liverpool had both Least Shots and Least Shots on Target, they managed to win only 1 game(against Chlesea), Drawn(against Everton) rest all Lost.


# Bar plot to see the Home Shots and Home shots on target by Opponent team against Liverpool while playing Away in 19-20 season.

fig = px.bar(Liverpool_away, y="home_team", x=["home_shots", "home_shots_on_target"], barmode='group',
             title='Total Away Shots and Shots On Target by all teams against Liverpool(Away) -',
             color_discrete_sequence=px.colors.qualitative.Antique_r)
fig.show()


# ------------------------------------Observation based on the graph---------------------------------------------

# Most no. of Shots against Liverpool are by Crystal Palace(16) followed by Manchester City(14), Watford(14), Tottenham(14) and Southampton(14).
# Most no. of Shots On Target against Liverpool are by Crystal Palace(6) and Manchester City(6) followed by Watford(5) then Tottenham(4). 
# Least no. of Shots against Liverpool are by Newcastle United(3), Arsenal(3), Leicester City(3) and AFC Bournemouth(3)
# Least no. of Shots On Target against Liverpool are by Norwich City(1) and most of the teams managed to only have 2 shots on target while playing at their respective Home, those teams are Newcastle United, Arsenal, Brighton, Aston Villa, Manchester United, Sheffield United, Chelsea and Burnley.

# Key-Point : Leicester City and AFC Bournemouth had 0 shots on target.
            # Despite having most no. of both Shot and Shot On Target, Crystal Palace could not win the match.


# Bar plot to see the Away Passes(made by Liverpool team) and Home Passes(made by opponent team) while playing Liverpool(Away) in 19-20 season.

fig = px.bar(Liverpool_away, y="home_team", x=["home_passes","away_passes"], barmode='group',
             title="Home Passes and Away Passes at Opponent Teams respective Home -",
             color_discrete_sequence=px.colors.qualitative.Set2)
fig.show()

# ------------------------------------Observation based on the graph---------------------------------------------

# Most passes Liverpool made were against AFC Bournemouth(852) followed by West Ham United(828), Newcastle United(792) and Tottenham(786).
# Least passes Liverpool made were against Chelsea(415) followed by Brighton(477) and Crystal Palace(510). 
# Most passes made by opponent team against Liverpool are 505 made by Wolves followed by Chelsea(492) and Manchester City(490).
# Least passes made by opponent team against Liverpool are 226 made by Aston Villa(226) followed by Everton(256) and Newcastle United(267).


# Dumbble Chart to compare Away Tackles(of Liverpool) vs Home Tackles

Liverpool_away.reset_index(drop=True, inplace=True)

fig = go.Figure()
fig.add_trace(go.Scatter(x = Liverpool_away["away_tackles"], 
                          y = Liverpool_away["home_team"],
                          mode = 'markers',
                          marker_color = 'red',
                          marker_size = 12,
                          name = 'Away Tackles'))
fig.add_trace(go.Scatter(x = Liverpool_away["home_tackles"], 
                          y = Liverpool_away["home_team"],
                          mode = 'markers',
                          marker_color = 'green', 
                          marker_size = 10,
                          name = 'Home Tackles'))
for i in range(0, len(Liverpool_home)):
               fig.add_shape(type='line',
                              x0 = Liverpool_away["away_tackles"][i],
                              y0 = i,
                              x1 = Liverpool_away["home_tackles"][i],
                              y1 = i,
                              line=dict(color='silver', width = 2))
fig.update_layout(title_text =
                    "Away Tackles vs Home Tackles -"
                    )
fig.show()

# ------------------------------------Observation based on the graph---------------------------------------------

# Most Away Tackles(made by Liverpool) were against Crystal Palace(24) followed by Tottenham(20) then Manchester United(18).
# Least Away Tackles(made by Liverpool) were against Southampton(7) followed by Watford(8) then AFC Bournemouth(10) and Leicester City(10).
# Most Home Tackles(made by Opponent) were by teams Newcastle United(23) followed by Arsenal(21) then Everton(20) and Aston Villa(20).
# Least Home Tackles(made by Opponent) were by teams Manchester City(10) and Manchester United(10).

# Key-Point : Thier were 3 games which ended with same no. of home and away tackles - Wolves vs Liverpool , West Ham United vs Liverpool and Sheffield United vs Liverpool.


# Dumbble Chart to compare Away Clearances vs Home Clearances

fig = go.Figure()
fig.add_trace(go.Scatter(x = Liverpool_away["away_clearances"], 
                          y = Liverpool_away["home_team"],
                          mode = 'markers',
                          marker_color = 'red',
                          marker_size = 12,
                          name = 'Away Clearances'))
fig.add_trace(go.Scatter(x = Liverpool_away["home_clearances"], 
                          y = Liverpool_away["home_team"],
                          mode = 'markers',
                          marker_color = 'purple', 
                          marker_size = 10,
                          name = 'Home Clearances'))
for i in range(0, len(Liverpool_away)):
               fig.add_shape(type='line',
                              x0 = Liverpool_away["away_clearances"][i],
                              y0 = i,
                              x1 = Liverpool_away["home_clearances"][i],
                              y1 = i,
                              line=dict(color='gold', width = 2))
fig.update_layout(title_text =
                    "Away Clearances vs Home Clearances -"
                    )
fig.show()

# ------------------------------------Observation based on the graph---------------------------------------------

# Most Away Clearances(made by Liverpool) were against Chelsea(37) followed by Southampton(30) and Crystal Palace(29).
# Least Away Clearances(made by Liverpool) were against Arsenal(3) and Everton(3) followed by AFC Bournemouth(5).
# Most Home Clearances(made by Opponent) were by teams Aston Villa(47) followed by Watford(41) then Brighton(39).
# Least Home Clearances(made by Opponent) were by teams Wolves(7) followed by Chelsea(10) then Manchester City(19) and West Ham United(19).

# Key-Point : Most attacking team against Liverpool was Chelsea at Chelsea's Home.


# Dumbble Chart to compare Away Corners vs Home Corners

fig = go.Figure()
fig.add_trace(go.Scatter(x = Liverpool_away["away_corners"], 
                          y = Liverpool_away["home_team"],
                          mode = 'markers',
                          marker_color = 'red',
                          marker_size = 12,
                          name = 'Away Corners'))
fig.add_trace(go.Scatter(x = Liverpool_away["home_corners"], 
                          y = Liverpool_away["home_team"],
                          mode = 'markers',
                          marker_color = 'maroon', 
                          marker_size = 10,
                          name = 'Home Corners'))
for i in range(0, len(Liverpool_away)):
               fig.add_shape(type='line',
                              x0 = Liverpool_away["away_corners"][i],
                              y0 = i,
                              x1 = Liverpool_away["home_corners"][i],
                              y1 = i,
                              line=dict(color='lime', width = 2))
fig.update_layout(title_text =
                    "Away Corners vs Home Corners -"
                    )
fig.show()

# ------------------------------------Observation based on the graph---------------------------------------------

# Most Away Corners(made by Liverpool) were against Arsenal(13) followed by Brighton(10) and Aston Villa(10).
# Least Away Corners(made by Liverpool) were against Manchester United(1) followed by Manchester City(3), Tottenham(3) and AFC Bournemouth(3).
# Most Home Corners(made by Opponent) were by teams Crystal Palace(9) followed by Brighton(6), Sheffiled United(6), Chelsea(6) and Burnley(6).
# Least Home Corners(made by Opponent) were by teams Everton(1) and AFC Bournemouth(1).


# Bar Plot to see the Away Fouls Conceded(including Yellow and Red Card) and Home Fouls Conceded(including Yellow and Red Card)

fig = px.bar(Liverpool_away, y="home_team", x=["away_fouls_conceded", "away_red_cards", "away_yellow_cards",
                                              "home_fouls_conceded", "home_red_cards", "home_yellow_cards"], 
             barmode='stack',
             title="Away Fouls vs Home Fouls Conceded (including Yellow and Red card) at Opponent's respective Home -",
             color_discrete_sequence=px.colors.qualitative.Set2)
fig.show()

# ------------------------------------Observation based on the graph---------------------------------------------

# Most Away Foul(made by Liverpool) are conceded against Burnley(16) followed by Brighton(15).
# Least Away Foul are conceded against Sheffield United(4) followed by Newcastle United(5).
# Most Yellow Card Liverpool got were against Brighton(4) followed by Chelsea(3).
# Liverpool got 0 Yellow Card against Newcastle United, Watford, West Ham United and Burnley.

# Most Home Fouls(made by Opponent team) were done by Everton(15) followed by Arsenal(14).
# Least Home Fouls were done by Watford(4), Tottenham(4) followed by Norwich City(5), Leicester City(5) and AFC Bournemouth(5).
# Home Team which conceded Most Yellow Card are Chelsea(3) and Arsenal(3).
# Least Yellow Card(0) conceded by Home team are Watford, Wolves, Tottenham, AFC Bournemout, Crystal Palace, Manchester United and Burnley,

# Key-Points : None of the team, neither Away Team(Liverpool) nor Home Teams got any Red card.
             # Matches with NO Yellow Card and Red Card - Watford vs Liverpool , Burnley vs Liverpool.


# Pie plot to see the match result when Liverpool played Away

print('List of Teams Liverpool won against at their respective Home-\n\n', Liverpool_away.groupby(['home_team','match_result']).size().reset_index().rename(columns={0:'Count'}))
print('-'*70)
print('\nNo. of matches Liverpool Won/Lost or Drawn -\n', Liverpool_away['match_result'].value_counts())

print('-'*70)

fig = px.pie(Liverpool_away, names='match_result' ,
            color_discrete_sequence=px.colors.sequential.Darkmint,
            title='Match Result when Liverpool played Away -')
fig.update_layout(
                    autosize=False,
                    width=550,
                    height=400
                )
fig.show()

# ------------------------------------Observation based on the graph---------------------------------------------

# Liverpool Won 14 Away matches out of 19, i.e, they won 73.7% matches.
# Liverpool drew only 2 matches out of all 19 ,against Everton and Manchester United.
# Liverpool Lost 3 Away matches, against Arsenal, Manchester City and Watford. Matches lost = 15.8%

List of Teams Liverpool won against at their respective Home-

                    home_team    match_result  Count
0            AFC Bournemouth   Liverpool Won      1
1                    Arsenal  Liverpool Lost      1
2                Aston Villa   Liverpool Won      1
3   Brighton and Hove Albion   Liverpool Won      1
4                    Burnley   Liverpool Won      1
5                    Chelsea   Liverpool Won      1
6             Crystal Palace   Liverpool Won      1
7                    Everton            Draw      1
8             Leicester City   Liverpool Won      1
9            Manchester City  Liverpool Lost      1
10         Manchester United            Draw      1
11          Newcastle United   Liverpool Won      1
12              Norwich City   Liverpool Won      1
13          Sheffield United   Liverpool Won      1
14               Southampton   Liverpool Won      1
15         Tottenham Hotspur   Liverpool Won      1
16                   Watford  Liverpool Lost      1
17           West Ham United   Liverpool Won      1
18   Wolverhampton Wanderers   Liverpool Won      1
----------------------------------------------------------------------

No. of matches Liverpool Won/Lost or Drawn -
 Liverpool Won     14
Liverpool Lost     3
Draw               2
Name: match_result, dtype: int64
----------------------------------------------------------------------


fig = px.pie(Liverpool_19_20_matches, names='match_result' ,
             color='match_result' ,
             color_discrete_map={'Liverpool Won':'mediumturquoise',
                                 'Draw':'grey',
                                 'Liverpool Lost':'gold'} ,
            title='Match Result of Liverpool when played Home and Away-')
fig.update_layout(
                    autosize=False,
                    width=500,
                    height=550
                )
fig.update_traces(textfont_size=18,
                  marker=dict(line=dict(color='#000000', width=2)))
fig.show()


# Cumulative total of points throughout the season of Liverpool and team played against Liverpool

Teams = Liverpool_19_20_matches['home_team'].unique()
TeamLists = {Team : [0] for Team in Teams}

for row in Liverpool_19_20_matches.itertuples():
    Home = row.home_team
    Away = row.away_team
    
    if row.home_score > row.away_score:
        TeamLists[Home].append(TeamLists[Home][-1]+3)
        TeamLists[Away].append(TeamLists[Away][-1]+0)
    elif row.home_score < row.away_score:
        TeamLists[Home].append(TeamLists[Home][-1]+0)
        TeamLists[Away].append(TeamLists[Away][-1]+3)
    else:
        TeamLists[Home].append(TeamLists[Home][-1]+1)
        TeamLists[Away].append(TeamLists[Away][-1]+1)


# Storing Liverpool points in a variable

Liverpool_points = TeamLists['Liverpool']
Liverpool_points

[0,
 3,
 6,
 9,
 12,
 15,
 18,
 21,
 24,
 25,
 28,
 31,
 34,
 37,
 40,
 43,
 46,
 49,
 52,
 55,
 58,
 61,
 64,
 67,
 70,
 73,
 76,
 79,
 79,
 82,
 83,
 86,
 86,
 89,
 92,
 93,
 93,
 96,
 99]


# Deleting 1st variable cause we want the points from 1st match itself 

Liverpool_points.pop(0)
Liverpool_points

[3,
 6,
 9,
 12,
 15,
 18,
 21,
 24,
 25,
 28,
 31,
 34,
 37,
 40,
 43,
 46,
 49,
 52,
 55,
 58,
 61,
 64,
 67,
 70,
 73,
 76,
 79,
 79,
 82,
 83,
 86,
 86,
 89,
 92,
 93,
 93,
 96,
 99]


# Creating a list from 1 to 38 as each team plays 38 no. of matches in a season

Matchday = list(range(1,39))
Matchday

[1,
 2,
 3,
 4,
 5,
 6,
 7,
 8,
 9,
 10,
 11,
 12,
 13,
 14,
 15,
 16,
 17,
 18,
 19,
 20,
 21,
 22,
 23,
 24,
 25,
 26,
 27,
 28,
 29,
 30,
 31,
 32,
 33,
 34,
 35,
 36,
 37,
 38]


fig = px.line(x=Matchday, y=Liverpool_points, hover_name=Liverpool_19_20_matches['match_result'],
              color_discrete_sequence = ['red'])

fig.update_layout(
     title={
        'text': "Liverpool Points Throughout the Season 2019-2020",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'},
        xaxis_title="Number Of Games -->",
        yaxis_title="Points -->",

    font=dict(
        family="Times New Roman",
        size=16,
        color="Navy"
            )
                )
fig['layout']['title']['font'] = dict(size=28)
fig.update_xaxes(title_font_family="Courier New")
fig.update_yaxes(title_font_family="Courier New")

fig.show()

	home_score	away_score	home_possession_%	away_possession_%	home_shots_on_target	away_shots_on_target	home_shots	away_shots	home_touches	away_touches	home_passes	away_passes	home_tackles	away_tackles	home_clearances	away_clearances	home_corners	away_corners	home_offsides	away_offsides	home_yellow_cards	away_yellow_cards	home_red_cards	away_red_cards	home_fouls_conceded	away_fouls_conceded
count	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000	380.000000
mean	1.515789	1.205263	49.922105	48.762105	4.510526	3.989474	13.134211	11.297368	649.642105	639.007895	455.515789	447.452632	16.028947	16.142105	18.021053	21.202632	5.692105	4.842105	1.771053	1.600000	1.565789	1.750000	0.063158	0.063158	10.289474	10.805263
std	1.248646	1.200252	13.970951	13.916075	2.589281	2.509064	5.618513	5.355292	153.601267	155.063958	145.188885	145.111386	5.479316	5.489815	8.982221	10.197702	3.266919	2.853746	1.517776	1.452139	1.249121	1.246896	0.254170	0.243567	3.750165	3.870458
min	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000
25%	1.000000	0.000000	41.400000	38.725000	3.000000	2.000000	9.000000	7.000000	552.000000	536.500000	358.750000	341.000000	13.000000	13.000000	12.000000	14.000000	3.000000	3.000000	1.000000	0.000000	1.000000	1.000000	0.000000	0.000000	8.000000	8.000000
50%	1.000000	1.000000	49.300000	49.850000	4.000000	4.000000	13.000000	11.000000	638.500000	636.500000	442.500000	441.500000	16.000000	16.000000	17.000000	20.000000	5.000000	5.000000	1.000000	1.000000	1.000000	2.000000	0.000000	0.000000	10.000000	11.000000
75%	2.000000	2.000000	60.725000	58.050000	6.000000	5.000000	16.000000	14.250000	747.250000	729.250000	542.250000	525.000000	20.000000	19.250000	23.000000	27.000000	8.000000	7.000000	3.000000	2.000000	2.000000	3.000000	0.000000	0.000000	13.000000	13.000000
max	8.000000	9.000000	80.200000	76.900000	13.000000	15.000000	31.000000	26.000000	1109.000000	1037.000000	969.000000	877.000000	36.000000	34.000000	57.000000	76.000000	17.000000	16.000000	9.000000	8.000000	6.000000	6.000000	2.000000	1.000000	23.000000	24.000000

	home_score	away_score	home_possession_%	away_possession_%	home_shots_on_target	away_shots_on_target	home_shots	away_shots	home_touches	away_touches	home_passes	away_passes	home_tackles	away_tackles	home_clearances	away_clearances	home_corners	away_corners	home_offsides	away_offsides	home_yellow_cards	away_yellow_cards	home_red_cards	away_red_cards	home_fouls_conceded	away_fouls_conceded
count	375.000000	375.000000	375.000000	375.000000	375.000000	375.000000	375.000000	375.000000	375.000000	375.000000	375.000000	375.000000	375.000000	375.000000	375.000000	375.000000	375.00000	375.000000	375.000000	375.000000	375.000000	375.000000	375.000000	375.00000	375.000000	375.000000
mean	1.514667	1.218667	50.587733	49.412267	4.570667	4.042667	13.309333	11.448000	658.304000	647.528000	461.589333	453.418667	16.242667	16.357333	18.261333	21.485333	5.76800	4.906667	1.794667	1.621333	1.586667	1.773333	0.064000	0.06400	10.426667	10.949333
std	1.253518	1.201680	12.807587	12.807587	2.553114	2.482730	5.445431	5.228147	134.875357	137.238945	136.200768	136.478880	5.190725	5.197212	8.795415	9.964599	3.22126	2.816934	1.513919	1.449903	1.244166	1.238566	0.255757	0.24508	3.580149	3.687686
min	0.000000	0.000000	23.100000	19.800000	0.000000	0.000000	2.000000	1.000000	408.000000	391.000000	226.000000	190.000000	5.000000	5.000000	1.000000	3.000000	0.00000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.00000	0.000000	1.000000
25%	1.000000	0.000000	41.750000	39.100000	3.000000	2.000000	10.000000	8.000000	556.000000	539.500000	362.000000	348.000000	13.000000	13.000000	12.000000	14.000000	3.00000	3.000000	1.000000	1.000000	1.000000	1.000000	0.000000	0.00000	8.000000	8.000000
50%	1.000000	1.000000	49.900000	50.100000	4.000000	4.000000	13.000000	11.000000	642.000000	639.000000	443.000000	443.000000	16.000000	16.000000	17.000000	20.000000	5.00000	5.000000	1.000000	1.000000	1.000000	2.000000	0.000000	0.00000	10.000000	11.000000
75%	2.000000	2.000000	60.900000	58.250000	6.000000	5.000000	16.000000	15.000000	748.500000	730.500000	544.000000	528.000000	20.000000	20.000000	23.000000	27.000000	8.00000	7.000000	3.000000	2.000000	2.000000	3.000000	0.000000	0.00000	13.000000	13.000000
max	8.000000	9.000000	80.200000	76.900000	13.000000	15.000000	31.000000	26.000000	1109.000000	1037.000000	969.000000	877.000000	36.000000	34.000000	57.000000	76.000000	17.00000	16.000000	9.000000	8.000000	6.000000	6.000000	2.000000	1.00000	23.000000	24.000000

Data Analysis and Visualization -¶

On Premiere League's 2019-2020 season.¶

EDA :¶

Analysing Liverpool team¶

Analysing Liverpool's Home Performance¶

Analysing Liverpool's AWAY performance¶

Data Visualization :¶

Visualizing Liverpool Home Stats¶

Visualizing Liverpool Away Stats¶

Liverpool's overall match result when played both Home and Away -¶

Points gained/dropped by Liverpool when played both Home and Away -¶

	date	home_team	away_team	home_score	away_score	home_possession_%	away_possession_%	home_shots_on_target	away_shots_on_target	home_shots	away_shots	home_touches	away_touches	home_passes	away_passes	home_tackles	away_tackles	home_clearances	away_clearances	home_corners	away_corners	home_offsides	away_offsides	home_yellow_cards	away_yellow_cards	away_red_cards	home_fouls_conceded	away_fouls_conceded
0	08/09/2019	Liverpool	Norwich City	4	1	57.9	42.1	7.0	5.0	15.0	12.0	662.0	577.0	477.0	363.0	21.0	12.0	5.0	35.0	11.0	2.0	0.0	5.0	0.0	2.0	0.0	9.0	9.0
1	08/10/2019	AFC Bournemouth	Sheffield United	1	1	52.9	47.1	3.0	3.0	13.0	8.0	671.0	615.0	485.0	428.0	18.0	14.0	13.0	16.0	3.0	4.0	1.0	1.0	2.0	1.0	0.0	10.0	19.0
2	08/10/2019	Burnley	Southampton	3	0	46.5	53.5	4.0	3.0	10.0	11.0	549.0	579.0	332.0	393.0	21.0	7.0	13.0	18.0	2.0	7.0	5.0	1.0	0.0	0.0	0.0	6.0	12.0
3	08/10/2019	Crystal Palace	Everton	0	0	35.4	64.6	2.0	3.0	6.0	10.0	467.0	722.0	268.0	500.0	21.0	14.0	21.0	18.0	6.0	2.0	4.0	0.0	2.0	1.0	1.0	16.0	14.0
4	08/11/2019	Leicester City	Wolverhampton Wanderers	0	0	70.0	30.0	1.0	2.0	16.0	8.0	871.0	508.0	665.0	291.0	20.0	19.0	12.0	33.0	12.0	3.0	0.0	1.0	0.0	2.0	0.0	3.0	13.0

	date	home_team	away_team	home_score	away_score
17	08/18/2019	Sheffield United	Crystal Palace	1	0
155	12/08/2019	Newcastle United	Southampton	2	1
322	07/04/2020	Leicester City	Crystal Palace	3	0
352	07/14/2020	Chelsea	Norwich City	1	0
360	07/21/2020	Aston Villa	Arsenal	1	0

	home_team	home_score	away_team	away_score	match_result	0
0	AFC Bournemouth	0	Liverpool	3	Liverpool Won	1
1	Arsenal	2	Liverpool	1	Liverpool Lost	1
2	Aston Villa	1	Liverpool	2	Liverpool Won	1
3	Brighton and Hove Albion	1	Liverpool	3	Liverpool Won	1
4	Burnley	0	Liverpool	3	Liverpool Won	1
5	Chelsea	1	Liverpool	2	Liverpool Won	1
6	Crystal Palace	1	Liverpool	2	Liverpool Won	1
7	Everton	0	Liverpool	0	Draw	1
8	Leicester City	0	Liverpool	4	Liverpool Won	1
9	Liverpool	1	Burnley	1	Draw	1
10	Liverpool	1	Wolverhampton Wanderers	0	Liverpool Won	1
11	Liverpool	2	AFC Bournemouth	1	Liverpool Won	1
12	Liverpool	2	Aston Villa	0	Liverpool Won	1
13	Liverpool	2	Brighton and Hove Albion	1	Liverpool Won	1
14	Liverpool	2	Leicester City	1	Liverpool Won	1
15	Liverpool	2	Manchester United	0	Liverpool Won	1
16	Liverpool	2	Sheffield United	0	Liverpool Won	1
17	Liverpool	2	Tottenham Hotspur	1	Liverpool Won	1
18	Liverpool	2	Watford	0	Liverpool Won	1
19	Liverpool	3	Arsenal	1	Liverpool Won	1
20	Liverpool	3	Manchester City	1	Liverpool Won	1
21	Liverpool	3	Newcastle United	1	Liverpool Won	1
22	Liverpool	3	West Ham United	2	Liverpool Won	1
23	Liverpool	4	Crystal Palace	0	Liverpool Won	1
24	Liverpool	4	Norwich City	1	Liverpool Won	1
25	Liverpool	4	Southampton	0	Liverpool Won	1
26	Liverpool	5	Chelsea	3	Liverpool Won	1
27	Liverpool	5	Everton	2	Liverpool Won	1
28	Manchester City	4	Liverpool	0	Liverpool Lost	1
29	Manchester United	1	Liverpool	1	Draw	1
30	Newcastle United	1	Liverpool	3	Liverpool Won	1
31	Norwich City	0	Liverpool	1	Liverpool Won	1
32	Sheffield United	0	Liverpool	1	Liverpool Won	1
33	Southampton	1	Liverpool	2	Liverpool Won	1
34	Tottenham Hotspur	0	Liverpool	1	Liverpool Won	1
35	Watford	3	Liverpool	0	Liverpool Lost	1
36	West Ham United	0	Liverpool	2	Liverpool Won	1
37	Wolverhampton Wanderers	1	Liverpool	2	Liverpool Won	1

	date	home_team	away_team	home_score	away_score	home_possession_%	away_possession_%	home_shots_on_target	away_shots_on_target	home_shots	away_shots	home_touches	away_touches	home_passes	away_passes	home_tackles	away_tackles	home_clearances	away_clearances	home_corners	away_corners	home_offsides	away_offsides	home_yellow_cards	away_yellow_cards	home_fouls_conceded	away_fouls_conceded	match_result
18	08/17/2019	Southampton	Liverpool	1	2	36.2	63.8	3.0	6.0	14.0	15.0	497.0	735.0	296.0	530.0	15.0	7.0	27.0	30.0	5.0	9.0	4.0	1.0	2.0	1.0	10.0	6.0	Liverpool Won
31	08/31/2019	Burnley	Liverpool	0	3	36.2	63.8	2.0	7.0	7.0	15.0	495.0	739.0	318.0	568.0	14.0	11.0	21.0	19.0	6.0	4.0	5.0	1.0	0.0	0.0	10.0	16.0	Liverpool Won
52	09/22/2019	Chelsea	Liverpool	1	2	55.0	45.0	2.0	3.0	13.0	6.0	713.0	608.0	492.0	415.0	15.0	11.0	10.0	37.0	6.0	4.0	7.0	1.0	3.0	3.0	8.0	13.0	Liverpool Won
67	09/28/2019	Sheffield United	Liverpool	0	1	29.6	70.4	2.0	4.0	12.0	16.0	479.0	896.0	291.0	708.0	11.0	11.0	29.0	25.0	6.0	5.0	0.0	1.0	1.0	1.0	8.0	4.0	Liverpool Won
86	10/20/2019	Manchester United	Liverpool	1	1	32.0	68.0	2.0	4.0	7.0	10.0	509.0	842.0	299.0	652.0	10.0	18.0	29.0	17.0	3.0	1.0	4.0	1.0	0.0	1.0	6.0	14.0	Draw
101	11/02/2019	Aston Villa	Liverpool	1	2	26.3	73.7	2.0	6.0	4.0	25.0	447.0	860.0	226.0	634.0	20.0	17.0	47.0	21.0	2.0	10.0	3.0	2.0	1.0	2.0	12.0	9.0	Liverpool Won
124	11/23/2019	Crystal Palace	Liverpool	1	2	40.0	60.0	6.0	4.0	16.0	12.0	544.0	703.0	330.0	510.0	14.0	24.0	31.0	29.0	9.0	8.0	3.0	0.0	0.0	1.0	8.0	7.0	Liverpool Won
151	12/07/2019	AFC Bournemouth	Liverpool	0	3	26.2	73.8	0.0	9.0	3.0	21.0	467.0	1017.0	305.0	852.0	12.0	10.0	35.0	5.0	1.0	3.0	5.0	1.0	0.0	1.0	5.0	6.0	Liverpool Won
179	01/29/2020	West Ham United	Liverpool	0	2	29.4	70.6	4.0	5.0	7.0	13.0	519.0	1007.0	331.0	828.0	17.0	17.0	19.0	12.0	3.0	7.0	1.0	0.0	2.0	0.0	6.0	6.0	Liverpool Won
185	12/26/2019	Leicester City	Liverpool	0	4	41.2	58.8	0.0	6.0	3.0	15.0	618.0	788.0	421.0	590.0	16.0	10.0	36.0	15.0	2.0	8.0	6.0	3.0	1.0	1.0	5.0	7.0	Liverpool Won
218	01/11/2020	Tottenham Hotspur	Liverpool	0	1	33.2	66.8	4.0	7.0	14.0	13.0	591.0	961.0	381.0	786.0	13.0	20.0	38.0	9.0	4.0	3.0	2.0	2.0	0.0	2.0	4.0	8.0	Liverpool Won
236	01/23/2020	Wolverhampton Wanderers	Liverpool	1	2	46.4	53.6	3.0	6.0	10.0	13.0	678.0	755.0	505.0	594.0	11.0	11.0	7.0	20.0	2.0	4.0	2.0	0.0	0.0	1.0	6.0	11.0	Liverpool Won
256	02/15/2020	Norwich City	Liverpool	0	1	36.7	63.3	1.0	6.0	5.0	17.0	571.0	801.0	373.0	624.0	17.0	16.0	33.0	7.0	2.0	7.0	1.0	0.0	1.0	2.0	5.0	11.0	Liverpool Won
278	02/29/2020	Watford	Liverpool	3	0	29.2	70.8	5.0	1.0	14.0	7.0	485.0	893.0	299.0	732.0	13.0	8.0	41.0	13.0	3.0	5.0	5.0	1.0	0.0	0.0	4.0	8.0	Liverpool Lost
293	06/21/2020	Everton	Liverpool	0	0	29.9	70.1	3.0	3.0	8.0	10.0	426.0	767.0	256.0	594.0	20.0	16.0	26.0	3.0	1.0	6.0	2.0	1.0	2.0	2.0	15.0	12.0	Draw
316	07/02/2020	Manchester City	Liverpool	4	0	47.0	53.0	6.0	3.0	14.0	11.0	662.0	709.0	490.0	551.0	10.0	13.0	19.0	8.0	3.0	3.0	3.0	2.0	2.0	2.0	8.0	7.0	Liverpool Lost
333	07/08/2020	Brighton and Hove Albion	Liverpool	1	3	44.4	55.6	2.0	8.0	12.0	20.0	594.0	667.0	381.0	477.0	12.0	11.0	39.0	18.0	6.0	10.0	5.0	0.0	1.0	4.0	7.0	15.0	Liverpool Won
350	07/15/2020	Arsenal	Liverpool	2	1	31.1	68.9	2.0	8.0	3.0	24.0	456.0	816.0	286.0	614.0	21.0	12.0	24.0	3.0	2.0	13.0	5.0	4.0	3.0	1.0	14.0	10.0	Liverpool Lost
377	07/26/2020	Newcastle United	Liverpool	1	3	25.3	74.7	2.0	6.0	3.0	14.0	428.0	981.0	267.0	792.0	23.0	12.0	23.0	8.0	2.0	4.0	3.0	1.0	1.0	0.0	11.0	5.0	Liverpool Won